Back to Annual Meeting Page		American Public Health Association 133rd Annual Meeting & Exposition December 10-14, 2005 Philadelphia, PA

Abstract #114540

Colleen M. Renier, BS¹, Susan G. Gerberich, PhD², Timothy R. Church, PhD², Ann S. Masten, PhD³, Kathleen Ferguson Carlson, MS⁴, Steven J. Mongin, MS², Andrew D. Ryan, MS⁵, and Bruce H. Alexander, PhD². (1) Division of Education & Research, St. Mary's/Duluth Clinic Health System, 5AV2ME, 400 E 3rd St, Duluth, MN 55805, 218-786-3834, crenier@smdc.org, (2) Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Mayo Mail Code 807, 420 Delaware St. SE, Minneapolis, MN 55455, (3) Institute of Child Development, Psychology, University of Minnesota, 51 East River Road, Minneapolis, MN 55455, (4) School of Public Health, Division of Environmental Health Sciences, Regional Injury Prevention Research Center, University of Minnesota, Mayo Mail Code 807, 420 Delaware Street S.E., Minneapolis, MN 55455, (5) Health Studies Section, University of Minnesota, Gateway Building Suite 350, 200 Oak St., Minneapolis, MN 55455

Background: This innovative model was designed to monitor changes, 1999 to 2001, in the incidence and consequences of injuries, for all ages, as well as risk factors for agriculture-related injuries incurred by children. Methods: Data collection was in two phases: Phase I, 1999; and Phase II (surveillance), 2001. A random sample of 16,000 agricultural operations was selected from the U.S. Department of Agriculture National Agricultural Statistics Service Master ListFrame in five midwest states (3,200 from each). Using a computer-assisted telephone interview (CATI), operations were screened for eligibility. A non-respondent survey was mailed to operations that had not participated. To optimize recall, two CATI interviews, each covering a 6-month portion of the year, included demographic and injury questions, as well as exposure questions through a nested case/control study. Cases were <20 years old (<20) people, with agriculture-related injuries. Controls were randomly selected, based upon a 6:1 ratio and the known probability of a <20 person incurring an agriculture-related injury. Reliability interviews were conducted on randomly selected households and people -- 100 for each interview section. Medical record validation was conducted on a 1:1 sample of agriculture-injured and non-injured <20 people. Results: Phase I and II identified similar samples. Phase I: 4,402 eligible operations; Household members, 51.6% male; Injuries, 47.0% agriculture-related; Controls, 56.8% male, 33.8% age 0-9. Phase II: 4,408 eligible operations; Household members, 51.7% male; Injuries, 45.5% agriculture-related; Controls, 54.3% male, 33.1% age 0-9. Implications: This innovative model for assessment and surveillance provides opportunities for development of interventions and further research.

Learning Objectives:

• Identify sampling and subsampling techniques beneficial to reliable agricultural operation surveillance.
• Identify characteristics of randomly sampled agricultural operation households with children.
• Recognize the importance of the unique surveillance system.

Keywords: Data/Surveillance, Injury Risk

Presenting author's disclosure statement:

I wish to disclose that I have NO financial interests or other relationship with the manufactures of commercial products, suppliers of commercial services or commercial supporters.

Recorded presentation